Sleep hygiene Post-Survey 5/6/2021

library(ggplot2)
library(dplyr)

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library(tidyverse)

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library(arsenal)
library(data.table)

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library(expss)

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sleephygiene <- read_csv("/Users/Ivanics/Desktop/SPH/4th term/HealthComm/Qualtrics post/Sleep Hygiene Post-Survey_May 6, 2021_13.37.csv")

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sleephygiene$StartDate <- lubridate::ymd_hms(sleephygiene$StartDate)

## Warning: 2 failed to parse.

#Filter to include only responses beyond this time
sleephygiene <- sleephygiene %>% filter(StartDate >= "2021-04-29 00:00:00")

#Select out the variables we need
sleephygiene <- sleephygiene %>% select(Progress, `Duration (in seconds)`, Finished, LocationLatitude, LocationLongitude, DistributionChannel, UserLanguage, Q1, Q2, Q3, Q2_5_TEXT, Q4, Q5, Q6, Q37, Q92, Q93, Q94,  Q38, Q39, Q10_2, Q10_3, Q9, Q61, Q84, Q85, Q81, Q63, Q96_1, Q96_2, Q96_3, Q96_4, Q96_5, Q96_6, Q96_7, Q96_8, Q95, Q83, Q82, Q69, Q62, Q64, Q90, Q91, Q89_1, Q67_1, Q67_2, Q67_3, Q75_1, Q75_2, Q75_3, Q68, Q70, Q70_18_TEXT, Q87, Q71, Q72, Q79, Q79_5_TEXT, Q74, Q73, Q73_5_TEXT, Q59_1, Q59_2, Q59_3, Q59_4, Q44_1, Q44_2, Q44_3, Q44_4, Q44_5, Q44_6, Q44_7, Q44_8, Q44_9, Q52)

sleephygiene <- rowid_to_column(sleephygiene, "ID")

#General factor recoding
sleephygiene <- sleephygiene %>% mutate(
  Q1_consent = factor(Q1)) %>%
  mutate(Q2_program = factor(Q2)) %>%
  mutate(Q3_role = factor(Q3)) %>%
  mutate(Q4_gender = factor(Q4)) %>%
  mutate(Q5_age = factor(Q5)) %>%
  mutate(Q6_numberinhousehold = as.numeric(Q6)) %>%
  mutate(Q37_employed = factor(Q37)) %>%
  mutate(Q92_notSPHemployed = factor(Q92)) %>%
  mutate(Q93_worksetting = factor(Q93)) %>%
  mutate(Q94_dayornight = factor(Q94)) %>%
  mutate(Q38_worksetting = factor(Q38)) %>%
  mutate(Q39_dayornight = factor(Q39)) %>%
  mutate(Q10_hoursofsleeplast5workdays = as.numeric(Q10_2)) %>%
  mutate(Q10_hoursofsleeppastweekend = as.numeric(Q10_3)) %>%
  mutate(Q9_howoftensleepypastmonth = factor(Q9)) %>%
  mutate(Q61_howoftensleepypasttwoweeks = factor(Q61)) %>%
  mutate(Q84_awareofhowtoimprovesleepquality = factor(Q84)) %>%
  mutate(Q81_seenorheardfromGNbloombergcampaign = factor(Q81)) %>%
  mutate(Q63_recalltoolsfreetect = factor(Q63)) %>%
  mutate(Q96_picture1 = factor(Q96_1)) %>%
  mutate(Q96_picture2 = factor(Q96_2)) %>%
  mutate(Q96_picture3 = factor(Q96_3)) %>%
  mutate(Q96_picture4 = factor(Q96_4)) %>%
  mutate(Q96_picture5 = factor(Q96_5)) %>%
  mutate(Q96_picture6 = factor(Q96_6)) %>%
  mutate(Q96_picture7 = factor(Q96_7)) %>%
  mutate(Q96_picture8 = factor(Q96_8)) %>%
  mutate(Q95_talkedtoanyone = factor(Q95)) %>%
  mutate(Q82_knowanyonewhoengaged = factor(Q82)) %>%
  mutate(Q69_didyouengagewiththecampaign = factor(Q69)) %>%
  mutate(Q90_areyouhappywithyoursleepquality_awareofcampaign = factor(Q90)) %>%
  mutate(Q91_areyouhappywithyoursleepquality_notawareofcampaign = factor(Q91)) %>%
  mutate(Q89_ratesleepquality_notawareofcampaign = factor(Q89_1)) %>%
  mutate(Q67_move30minutes = as.numeric(Q67_1)) %>%
  mutate(Q67_breathing = as.numeric(Q67_2)) %>%
  mutate(Q67_powerdown = as.numeric(Q67_2)) %>%
  mutate(Q75_moving = factor(Q75_1)) %>%
  mutate(Q75_breathing = factor(Q75_2)) %>%
  mutate(Q75_powerdown = factor(Q75_3)) %>%
  mutate(Q68_timing = factor(Q68)) %>%
  mutate(Q87_idealtime = factor(Q87)) %>%
  mutate(Q74_rafflemotivating = factor(Q74)) %>%
  mutate(Q75_moving = factor(Q75_1)) %>%
  mutate(Q59_canmaintainhealthysleephabits = factor(Q59_1)) %>%
  mutate(Q59_cancutoutscreen = factor(Q59_2)) %>%
  mutate(Q59_canexercise = factor(Q59_3)) %>%
  mutate(Q59_canparticipateinbreathing = factor(Q59_4)) %>%
  mutate(Q44_goodnightsleepisimportant = factor(Q44_1)) %>%
  mutate(Q44_mentalclarity = factor(Q44_2)) %>%
  mutate(Q44_feelpositive = factor(Q44_3)) %>%
  mutate(Q44_cuttingoutscreenleadstobettersleep = factor(Q44_4)) %>%
  mutate(Q44_exercisingleadstobettersleep = factor(Q44_5)) %>%
  mutate(Q44_breathingexercisesleadstobettersleep = factor(Q44_6)) %>%
  mutate(Q44_iwillstopscreens = factor(Q44_7)) %>%
  mutate(Q44_iwillexercise = factor(Q44_8)) %>%
  mutate(Q44_iwillbreathe = factor(Q44_9)) %>%
  mutate(Q52_additionalcomments = factor(Q52))

#Q85
resp.split_85 <- strsplit(sleephygiene$Q85, ",")
lev <- unique(unlist(resp.split_85))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_85, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q85_waystoimprovesleepquality = case_when(
    Not.drinking.caffeinated.beverages.late.in.the.day == 1 ~ "Not drinking caffeinated beverages late in the day",
    Switching.off.electronics.one.hour.before.sleep == 1 ~ "Switching off electronics one hour before sleep",
    Incorporating.moderate.exercise.as.part.of.your.day == 1 ~ "Incorporating moderate exercise as part of your day",
    Increase.natural.bright.light.exposure.in.the.day == 1 ~ "Increase natural bright light exposure in the day",
    Reduce.irregular.or.long.daytime.naps == 1 ~ "Reduce irregular or long daytime naps",
    Try.to.sleep.and.wake.at.consistent.times == 1 ~ "Try to sleep and wake at consistent times",
    Take.a.melatonin.supplement == 1 ~ "Take a melatonin supplement",
    Decrease.alcohol.consumption == 1 ~ "Decrease alcohol consumption",
    Deep.breathing.exercises == 1 ~ "Deep breathing exercises"))

#Q83
resp.split_83 <- strsplit(sleephygiene$Q83, ",")
lev <- unique(unlist(resp.split_83))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_83, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q83_talkedtowho = case_when(
    Friends == 1 ~ "Friends",
    Spouse == 1 ~ "Spouse",
    Relatives == 1 ~ "Relatives",
    Colleague == 1 ~ "Colleague"))

#Q62
resp.split_62 <- strsplit(sleephygiene$Q62, ",")
lev <- unique(unlist(resp.split_62))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_62, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q62_howdidyouengage = case_when(
    Instagram.campaign == 1 ~ "Instagram campaign",
    Text.message.campaign == 1 ~ "Text message campaign",
    Word.of.mouth.discussion.with.others == 1 ~ "Word of mouth/discussion with others"))

#64
resp.split_64 <- strsplit(sleephygiene$Q64, ",")
lev <- unique(unlist(resp.split_64))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_64, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q64_whichtechniquedidyoutry = case_when(
    X.MoveMore == 1 ~ "Movemore",
    X.Breathe== 1 ~ "Breathe",
    X.PowerDown == 1 ~ "Powerdown",
    None.of.the.above == 1 ~ "None of the above"))

#70
resp.split_70 <- strsplit(sleephygiene$Q70, ",")
lev <- unique(unlist(resp.split_70))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_70, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q70_timingoftextsinconvenient = case_when(
    #Messages.were.too.frequent == 1 ~ "Messages were too frequent",
    Messages.were.too.infrequent== 1 ~ "Messages were too infrequent",
    Received.message.too.early.in.the.day == 1 ~ "Received message too early in the day",
    #Received.message.too.late.in.the.day == 1 ~ "Received message too late in the day",
    Other..please.explain.below. == 1 ~ "Other (please explain below)"))

#71
resp.split_71 <- strsplit(sleephygiene$Q71, ",")
lev <- unique(unlist(resp.split_71))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_71, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q71_whichchannelmosteducational = case_when(
    Text == 1 ~ "Text",
    Instagram == 1 ~ "Instagram"))
    #Discussion.with.others.about.the.campaign == 1 ~ "Discussion with others about the campaign",
    #None.of.the.above.1 == 1 ~ "None of the above"))

#72 - look into


#Q79
resp.split_79 <- strsplit(sleephygiene$Q79, ",")
lev <- unique(unlist(resp.split_79))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_79, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q79_moresuccessfuloutcomsuggestions = case_when(
    There.was.an.in.person.on.campus.component.to.the.campaign == 1 ~ "There was an in-person/on-campus component to the campaign",
    The.campaign.was.longer == 1 ~ "The campaign was longer",
    I.had.more.flexibility.in.my.day == 1 ~ "I had more flexibility in my day",
    There.were.subject.matter.experts.checking.in.with.me.one.on.one == 1 ~ "There were subject matter experts checking in with me one-on-one"))
    #Other == 1 ~ "Reduce irregular or long daytime naps",

#Q73
resp.split_73 <- strsplit(sleephygiene$Q73, ",")
lev <- unique(unlist(resp.split_73))
sleephygiene<- with(sleephygiene, data.frame(sleephygiene, t(sapply(resp.split_73, function(x) table(factor(x, levels=lev))))))

sleephygiene <- sleephygiene %>%
    mutate(Q73_hearabouthow = case_when(
    Instagram.1 == 1 ~ "Instagram",
    JHSPH.Activities.email == 1 ~ "JHSPH Activities email",
    #Class.announcement == 1 ~ "Class announcement",
    Word.of.mouth.discussion.with.others.1 == 1 ~ "Word of mouth/discussion with others"))
    #Other == 1 ~ "Reduce irregular or long daytime naps",

Plots for wakeup and sleep times

library(plotly)

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workdayssleep <- sleephygiene %>% ggplot( aes(x=Q10_hoursofsleeplast5workdays)) +
    geom_histogram( binwidth=1, fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Hours of sleep last five workdays") +
    theme(
      plot.title = element_text(size=32)
    ) +
  labs(x="Number of hours of sleep in the past five workdays", y="Number of participants")
ggplotly(workdayssleep)

## Warning: Removed 4 rows containing non-finite values (stat_bin).

#Plot for weekend
weekend <- sleephygiene %>% ggplot( aes(x=Q10_hoursofsleeppastweekend)) +
    geom_histogram( binwidth=1, fill="#69b3a2", color="#e9ecef", alpha=0.9) +
    ggtitle("Hours of sleep last weekend") +
    theme(
      plot.title = element_text(size=32)
    ) +
  labs(x="Number of hours of sleep in the past weekend", y="Number of participants")
ggplotly(weekend)

## Warning: Removed 4 rows containing non-finite values (stat_bin).

#Tab 1
sleephygiene$Q9_howoftensleepypastmonth <- factor(sleephygiene$Q9_howoftensleepypastmonth, levels = c("Never", "Rarely", "Sometimes", "Very often", "Always"))
sleephygiene$Q61_howoftensleepypasttwoweeks <- factor(sleephygiene$Q61_howoftensleepypasttwoweeks, levels = c("Never", "Rarely", "Sometimes", "Very often", "Always"))
sleephygiene$Q89_ratesleepquality_notawareofcampaign <- factor(sleephygiene$Q89_ratesleepquality_notawareofcampaign, levels = c("Poor", "Fair", "Good", "Excellent"))
sleephygiene$Q75_moving <- factor(sleephygiene$Q75_moving, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q75_breathing <- factor(sleephygiene$Q75_breathing, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q75_powerdown <- factor(sleephygiene$Q75_powerdown, levels = c("Extremely unhelpful", "Somewhat unhelpful", "Neither helpful nor unhelpful", "Somewhat helpful", "Extremely helpful"))
sleephygiene$Q87_idealtime <- factor(sleephygiene$Q87_idealtime, levels = c("Early morning (6:00 am - 9:00 am)", "Late morning (9:01 am - 12:00 pm)", "Early afternoon (12:01 pm - 3:00 pm)", "Late afternoon (3:01 pm - 6:00 pm)", "Early evening (6:01 pm - 9:00 pm)", "Late evening (9:01 pm - 12:00 am)", "Other (please specify)"))
sleephygiene$Q59_canmaintainhealthysleephabits <- factor(sleephygiene$Q59_canmaintainhealthysleephabits, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_cancutoutscreen <- factor(sleephygiene$Q59_cancutoutscreen, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_canexercise <- factor(sleephygiene$Q59_canexercise, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q59_canparticipateinbreathing <- factor(sleephygiene$Q59_canparticipateinbreathing, levels = c("Not at all confident", "Somewhat confident", "Extremely confident"))
sleephygiene$Q44_goodnightsleepisimportant <- factor(sleephygiene$Q44_goodnightsleepisimportant, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_mentalclarity <- factor(sleephygiene$Q44_mentalclarity, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_feelpositive <- factor(sleephygiene$Q44_feelpositive, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_cuttingoutscreenleadstobettersleep <- factor(sleephygiene$Q44_cuttingoutscreenleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_exercisingleadstobettersleep <- factor(sleephygiene$Q44_exercisingleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_breathingexercisesleadstobettersleep <- factor(sleephygiene$Q44_breathingexercisesleadstobettersleep, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillstopscreens <- factor(sleephygiene$Q44_iwillstopscreens, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillexercise <- factor(sleephygiene$Q44_iwillexercise, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))
sleephygiene$Q44_iwillbreathe <- factor(sleephygiene$Q44_iwillbreathe, levels = c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree"))

library(expss)
sleephygiene = apply_labels(sleephygiene,
                      Q3_role = "What is your role at Bloomberg",
                      Q4_gender = "Which best describes your gender identity?",
                      Q2_program = "What is your current program at Bloomberg?",
                      Q5_age = "How old are you?",
                      Q6_numberinhousehold = "How many people live in your household, including yourself?",
                      Q37_employed = "If you are a student at Bloomberg, are you currently employed outside of your education program?",
                      Q92_notSPHemployed = "Are you currently employed?",
                      Q93_worksetting = "Which of the following best describes your current work setting?",
                      Q94_dayornight = "Do you work day or night shifts?",
                      Q38_worksetting = "Which of the following best describes your current work setting?",
                      Q39_dayornight = "Do you work day or night shifts?",
                      Q10_hoursofsleeplast5workdays = "On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?",
                      Q10_hoursofsleeppastweekend = "On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?",
                      Q9_howoftensleepypastmonth = "How often did you feel sleepy during the day in the past month?",
                      Q61_howoftensleepypasttwoweeks = "How often did you feel sleepy during the day during the past 2 weeks?",
                      Q84_awareofhowtoimprovesleepquality = "Do you know any ways a person can improve their sleep quality?",
                      Q85_waystoimprovesleepquality = "What are some of the ways to improve sleep quality that you know?",
                      Q81_seenorheardfromGNbloombergcampaign = "In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?",
                      Q63_recalltoolsfreetect = "Can you recall any specific tools, techniques, or resources from the campaign? Please describe below.",
                      Q96_picture1 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1",
                      Q96_picture2 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2",
                      Q96_picture3 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3",
                      Q96_picture4 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4",
                      Q96_picture5 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5",
                      Q96_picture6 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6",
                      Q96_picture7 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7",
                      Q96_picture8 = "Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8",
                      Q95_talkedtoanyone = "Have you talked to anyone about the #GoodnightBloomberg campaign?",
                      Q83_talkedtowho = "Please indicate with whom you talked about #GoodnightBloomberg (check all that apply).",
                      Q82_knowanyonewhoengaged = "Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?",
                      Q69_didyouengagewiththecampaign = "Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?",
                      Q62_howdidyouengage = "Please select which of the following parts of the #GoodnightBloomberg campaign you engaged in:",
                      Q64_whichtechniquedidyoutry = "Which of the following techniques did you try at least once in the last 2 weeks (choose all that apply)?", 
                      Q90_areyouhappywithyoursleepquality_awareofcampaign = "Are you happy with your sleep quality overall currently?", 
                      Q91_areyouhappywithyoursleepquality_notawareofcampaign = "Are you happy with your sleep quality overall currently?", 
                      Q89_ratesleepquality_notawareofcampaign = "Please rate your sleep quality from the following options: In the last two weeks? (on average)",
                      Q67_move30minutes =  "In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day",
                      Q67_breathing = "In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise",
                      Q67_powerdown = "In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed",
                      Q75_moving = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Moving 30 minutes total per day",
                      Q75_breathing = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Using a breathing exercise",
                      Q75_powerdown = "How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Powering down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed",
                      Q68_timing = "Was the timing of the texts/posts convenient for you to adopt the recommended activity? ",
                      Q70_timingoftextsinconvenient = "Please provide information below about why the timing of the texts/posts was inconvenient?", 
                      Q87_idealtime = "What would have been the ideal time to receive the message (EST/EDT)?",
                      Q71_whichchannelmosteducational = "Which channel did you find the most educational?",
                      Q79_moresuccessfuloutcomsuggestions = "I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):",
                      Q74_rafflemotivating = "Did you find the raffles motivating for participation in the #GoodnightBloomberg campaign?",
                      Q73_hearabouthow = "How did you hear about the #GoodnightBloomberg campaign?",
                      Q59_canmaintainhealthysleephabits = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.",
                      Q59_cancutoutscreen = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.",
                      Q59_canexercise = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.", 
                      Q59_canparticipateinbreathing = "Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.", 
                      Q44_goodnightsleepisimportant = "Please rate your agreement with the following statements: Getting a good night's sleep is important to me.",
                      Q44_mentalclarity = "Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.",
                      Q44_feelpositive = "Please rate your agreement with the following statements: I feel positive about the quality of my sleep.",
                      Q44_cuttingoutscreenleadstobettersleep = "Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.",
                      Q44_exercisingleadstobettersleep = "Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.",
                      Q44_breathingexercisesleadstobettersleep = "Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.",
                      Q44_iwillstopscreens = "Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.",
                      Q44_iwillexercise = "Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.",
                      Q44_iwillbreathe = "Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.",
                      Q52_additionalcomments = "Please share any additional comments or feedback you have about the #GoodnightBloomberg sleep campaign below."
                      )

attach(sleephygiene)
tab1 <- tableby(~ Q3_role + 
                  Q4_gender +
                  Q5_age +
                  Q6_numberinhousehold +
                  Q37_employed +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q9_howoftensleepypastmonth +
                  Q61_howoftensleepypasttwoweeks +
                  Q84_awareofhowtoimprovesleepquality +
                  Q81_seenorheardfromGNbloombergcampaign +
                  #Q63_recalltoolsfreetect +
                  Q96_picture1 +
                  Q96_picture2 +
                  Q96_picture3 +
                  Q96_picture4 +
                  Q96_picture5 +
                  Q96_picture6 +
                  Q96_picture7 +
                  Q96_picture8 +
                  Q95_talkedtoanyone +
                  Q82_knowanyonewhoengaged +
                  Q69_didyouengagewiththecampaign +
                  Q67_move30minutes +
                  Q67_breathing +
                  Q67_powerdown +
                  Q68_timing + 
                  Q79_moresuccessfuloutcomsuggestions +
                  Q59_canmaintainhealthysleephabits +
                  Q59_cancutoutscreen +
                  Q59_canexercise +
                  Q59_canparticipateinbreathing +
                  Q44_goodnightsleepisimportant +
                  Q44_mentalclarity +
                  Q44_feelpositive +
                  Q44_cuttingoutscreenleadstobettersleep +
                  Q44_exercisingleadstobettersleep +
                  Q44_breathingexercisesleadstobettersleep +
                  Q44_iwillstopscreens +
                  Q44_iwillexercise +
                  Q44_iwillbreathe,
                data=sleephygiene, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=149)
What is your role at Bloomberg
N-Miss	4
Faculty/Staff Member	9 (6.2%)
Full-time student	82 (56.6%)
Not affiliated with Bloomberg School of Public Health	1 (0.7%)
Part-time student	53 (36.6%)
Which best describes your gender identity?
N-Miss	4
Female	121 (83.4%)
Male	23 (15.9%)
Non-binary / third gender	1 (0.7%)
How old are you?
N-Miss	4
18-25	44 (30.3%)
26-34	63 (43.4%)
35-44	24 (16.6%)
45-54	12 (8.3%)
55-64	1 (0.7%)
64-75	1 (0.7%)
How many people live in your household, including yourself?
Median (Q1, Q3)	2.00 (2.00, 3.00)
If you are a student at Bloomberg, are you currently employed outside of your education program?
N-Miss	4
N/A - I am not a student at Bloomberg	9 (6.2%)
No	66 (45.5%)
Yes	70 (48.3%)
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?
Median (Q1, Q3)	7.00 (6.00, 7.00)
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?
Median (Q1, Q3)	8.00 (7.00, 8.00)
How often did you feel sleepy during the day in the past month?
N-Miss	56
Never	3 (3.2%)
Rarely	14 (15.1%)
Sometimes	66 (71.0%)
Very often	0 (0.0%)
Always	10 (10.8%)
How often did you feel sleepy during the day during the past 2 weeks?
N-Miss	54
Never	2 (2.1%)
Rarely	23 (24.2%)
Sometimes	54 (56.8%)
Very often	0 (0.0%)
Always	16 (16.8%)
Do you know any ways a person can improve their sleep quality?
N-Miss	5
No	7 (4.9%)
Yes	137 (95.1%)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?
N-Miss	5
Don’t know	33 (22.9%)
No	57 (39.6%)
Yes	54 (37.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1
N-Miss	22
No	24 (18.9%)
Not sure	97 (76.4%)
Yes	6 (4.7%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2
N-Miss	17
No	7 (5.3%)
Not sure	76 (57.6%)
Yes	49 (37.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3
N-Miss	21
No	20 (15.6%)
Not sure	101 (78.9%)
Yes	7 (5.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4
N-Miss	22
No	18 (14.2%)
Not sure	98 (77.2%)
Yes	11 (8.7%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5
N-Miss	20
No	14 (10.9%)
Not sure	97 (75.2%)
Yes	18 (14.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6
N-Miss	20
No	19 (14.7%)
Not sure	106 (82.2%)
Yes	4 (3.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7
N-Miss	20
No	17 (13.2%)
Not sure	100 (77.5%)
Yes	12 (9.3%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8
N-Miss	21
No	18 (14.1%)
Not sure	104 (81.2%)
Yes	6 (4.7%)
Have you talked to anyone about the #GoodnightBloomberg campaign?
N-Miss	5
No	131 (91.0%)
Yes	13 (9.0%)
Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?
N-Miss	5
No	134 (93.1%)
Yes	10 (6.9%)
Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?
N-Miss	5
No	119 (82.6%)
Yes	25 (17.4%)
In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day
Median (Q1, Q3)	9.00 (5.00, 12.00)
In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise
Median (Q1, Q3)	2.50 (1.00, 6.00)
In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed
Median (Q1, Q3)	2.50 (1.00, 6.00)
Was the timing of the texts/posts convenient for you to adopt the recommended activity?
N-Miss	34
No	54 (47.0%)
Yes	61 (53.0%)
I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):
N-Miss	47
I had more flexibility in my day	42 (41.2%)
The campaign was longer	24 (23.5%)
There was an in-person/on-campus component to the campaign	25 (24.5%)
There were subject matter experts checking in with me one-on-one	11 (10.8%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.
N-Miss	7
Not at all confident	26 (18.3%)
Somewhat confident	86 (60.6%)
Extremely confident	30 (21.1%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.
N-Miss	7
Not at all confident	70 (49.3%)
Somewhat confident	54 (38.0%)
Extremely confident	18 (12.7%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.
N-Miss	7
Not at all confident	18 (12.7%)
Somewhat confident	61 (43.0%)
Extremely confident	63 (44.4%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.
N-Miss	7
Not at all confident	17 (12.0%)
Somewhat confident	75 (52.8%)
Extremely confident	50 (35.2%)
Please rate your agreement with the following statements: Getting a good night’s sleep is important to me.
N-Miss	7
Strongly disagree	0 (0.0%)
Somewhat disagree	1 (0.7%)
Neither agree nor disagree	1 (0.7%)
Somewhat agree	25 (17.6%)
Strongly agree	115 (81.0%)
Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.
N-Miss	7
Strongly disagree	0 (0.0%)
Somewhat disagree	1 (0.7%)
Neither agree nor disagree	0 (0.0%)
Somewhat agree	23 (16.2%)
Strongly agree	118 (83.1%)
Please rate your agreement with the following statements: I feel positive about the quality of my sleep.
N-Miss	7
Strongly disagree	11 (7.7%)
Somewhat disagree	33 (23.2%)
Neither agree nor disagree	23 (16.2%)
Somewhat agree	52 (36.6%)
Strongly agree	23 (16.2%)
Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.
N-Miss	6
Strongly disagree	1 (0.7%)
Somewhat disagree	5 (3.5%)
Neither agree nor disagree	19 (13.3%)
Somewhat agree	50 (35.0%)
Strongly agree	68 (47.6%)
Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.
N-Miss	6
Strongly disagree	0 (0.0%)
Somewhat disagree	2 (1.4%)
Neither agree nor disagree	5 (3.5%)
Somewhat agree	40 (28.0%)
Strongly agree	96 (67.1%)
Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.
N-Miss	6
Strongly disagree	0 (0.0%)
Somewhat disagree	5 (3.5%)
Neither agree nor disagree	36 (25.2%)
Somewhat agree	57 (39.9%)
Strongly agree	45 (31.5%)
Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.
N-Miss	8
Strongly disagree	27 (19.1%)
Somewhat disagree	27 (19.1%)
Neither agree nor disagree	28 (19.9%)
Somewhat agree	41 (29.1%)
Strongly agree	18 (12.8%)
Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.
N-Miss	7
Strongly disagree	3 (2.1%)
Somewhat disagree	8 (5.6%)
Neither agree nor disagree	17 (12.0%)
Somewhat agree	49 (34.5%)
Strongly agree	65 (45.8%)
Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.
N-Miss	7
Strongly disagree	12 (8.5%)
Somewhat disagree	21 (14.8%)
Neither agree nor disagree	26 (18.3%)
Somewhat agree	55 (38.7%)
Strongly agree	28 (19.7%)

#If student
student <- sleephygiene %>% filter(Q3_role %in% c("Part-time student", "Full-time student"))

tab2 <- tableby(~ Q2_program,
                data=student, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab2, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=135)
What is your current program at Bloomberg?
Doctoral Student	29 (21.5%)
Masters Student	90 (66.7%)
Other	6 (4.4%)
Post-doctoral student	10 (7.4%)

#If employed 
nonbloombergstudentemployed <- sleephygiene %>% filter(Q37_employed == "N/A - I am not a student at Bloomberg")

tab3 <- tableby(~ Q92_notSPHemployed,
                data=nonbloombergstudentemployed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab3, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=9)
Are you currently employed?
Yes	9 (100.0%)

#If employed and not bloomberg
employed <- nonbloombergstudentemployed %>% filter(Q92_notSPHemployed == "Yes")

tab4 <- tableby(~ Q93_worksetting,
                data=employed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab4, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=9)
Which of the following best describes your current work setting?
I sometimes work at home and sometimes at another location	3 (33.3%)
I work from home	5 (55.6%)
I work in a location away from my home	1 (11.1%)

#wfh not bloomberg
#wfhnotbloomberg <- nonbloombergstudentemployed %>% filter(Q93_worksetting == "I work in a location away from my home")

#tab5 <- tableby(~ Q94_dayornight,
#                data=wfhnotbloomberg, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab5, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

#student at bloomberg
studentemployed <- student %>% filter(Q37_employed == "Yes")

tab6 <- tableby(~ Q38_worksetting,
                data=studentemployed, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab6, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=70)
Which of the following best describes your current work setting?
N-Miss	2
I sometimes work at home and sometimes at another location	16 (23.5%)
I work from home	40 (58.8%)
I work in a location away from my home	12 (17.6%)

studentemployedlocation <- student %>% filter(Q39_dayornight == "I work in a location away from my home")

#tab7 <- tableby(~ Q39_dayornight,
#                data=studentemployedlocation, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab7, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)


#Aware of how to improve sleep quality
awareofsleepqualityimprovements <- sleephygiene %>% filter(Q84_awareofhowtoimprovesleepquality == "Yes")

tab8 <- tableby(~ Q85_waystoimprovesleepquality,
                data=awareofsleepqualityimprovements, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab8, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=137)
What are some of the ways to improve sleep quality that you know?
N-Miss	1
Not drinking caffeinated beverages late in the day	127 (93.4%)
Reduce irregular or long daytime naps	1 (0.7%)
Switching off electronics one hour before sleep	7 (5.1%)
Try to sleep and wake at consistent times	1 (0.7%)

#Talked to someone
talkedtosomeone <- sleephygiene %>% filter(Q95_talkedtoanyone == "Yes")

tab9 <- tableby(~ Q83_talkedtowho,
                data=talkedtosomeone, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab9, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=13)
Please indicate with whom you talked about #GoodnightBloomberg (check all that apply).
N-Miss	1
Colleague	1 (8.3%)
Friends	9 (75.0%)
Spouse	2 (16.7%)

#engaged in any way
engagedwiththecampaign <- sleephygiene %>% filter(Q69_didyouengagewiththecampaign == "Yes")

tab10 <- tableby(~ Q62_howdidyouengage +
                   Q64_whichtechniquedidyoutry +
                   Q90_areyouhappywithyoursleepquality_awareofcampaign +
                   Q75_moving +
                   Q75_breathing +
                   Q75_powerdown,
                data=engagedwiththecampaign, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab10, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=25)
Please select which of the following parts of the #GoodnightBloomberg campaign you engaged in:
N-Miss	1
Instagram campaign	15 (62.5%)
Text message campaign	8 (33.3%)
Word of mouth/discussion with others	1 (4.2%)
Which of the following techniques did you try at least once in the last 2 weeks (choose all that apply)?
Breathe	5 (20.0%)
Movemore	15 (60.0%)
None of the above	2 (8.0%)
Powerdown	3 (12.0%)
Are you happy with your sleep quality overall currently?
N-Miss	1
No	10 (41.7%)
Yes	14 (58.3%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Moving 30 minutes total per day
N-Miss	8
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	0 (0.0%)
Somewhat helpful	13 (76.5%)
Extremely helpful	4 (23.5%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Using a breathing exercise
N-Miss	12
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	7 (53.8%)
Somewhat helpful	4 (30.8%)
Extremely helpful	2 (15.4%)
How helpful did you find the following activities for getting better quality sleep in the past 2 weeks? Powering down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed
N-Miss	16
Extremely unhelpful	0 (0.0%)
Somewhat unhelpful	0 (0.0%)
Neither helpful nor unhelpful	2 (22.2%)
Somewhat helpful	5 (55.6%)
Extremely helpful	2 (22.2%)

#did not engagee in any way
noengagementwiththecampagin <- sleephygiene %>% filter(Q69_didyouengagewiththecampaign %in% c("No", "Don't know"))

tab11 <- tableby(~ Q91_areyouhappywithyoursleepquality_notawareofcampaign +
                   Q89_ratesleepquality_notawareofcampaign,
                data=noengagementwiththecampagin, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab11, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=119)
Are you happy with your sleep quality overall currently?
N-Miss	32
No	52 (59.8%)
Yes	35 (40.2%)
Please rate your sleep quality from the following options: In the last two weeks? (on average)
N-Miss	30
Poor	9 (10.1%)
Fair	38 (42.7%)
Good	37 (41.6%)
Excellent	5 (5.6%)

#not convenient 
notconvenient <- sleephygiene %>% filter(Q68_timing == "No")

tab12 <- tableby(~ Q70_timingoftextsinconvenient,
                data=noengagementwiththecampagin, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab12, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=119)
Please provide information below about why the timing of the texts/posts was inconvenient?
N-Miss	86
Messages were too infrequent	5 (15.2%)
Other (please explain below)	27 (81.8%)
Received message too early in the day	1 (3.0%)

#tooearlyintheday
tooearlyortoolate <- notconvenient %>% filter(Q70_timingoftextsinconvenient %in% c("Received message too early in the day", "Received message too late in the day"))

tab13 <- tableby(~ Q87_idealtime,
                data=tooearlyortoolate, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab13, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=3)
What would have been the ideal time to receive the message (EST/EDT)?
Early morning (6:00 am - 9:00 am)	0 (0.0%)
Late morning (9:01 am - 12:00 pm)	1 (33.3%)
Early afternoon (12:01 pm - 3:00 pm)	0 (0.0%)
Late afternoon (3:01 pm - 6:00 pm)	0 (0.0%)
Early evening (6:01 pm - 9:00 pm)	2 (66.7%)
Late evening (9:01 pm - 12:00 am)	0 (0.0%)
Other (please specify)	0 (0.0%)

#whichmosteducational
instagramortext <- engagedwiththecampaign %>% filter(Q62_howdidyouengage %in% c("Instagram", "Text message campaign"))

#tab14 <- tableby(~ Q71_whichchannelmosteducational +
#                   Q72,
#                data=instagramortext, test=TRUE, total=TRUE, 
#                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
#summary(tab14, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

#instagram
instagram <- engagedwiththecampaign %>% filter(Q62_howdidyouengage == "Instagram campaign")

tab15 <- tableby(~ Q74_rafflemotivating,
                data=instagram, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab15, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=15)
Did you find the raffles motivating for participation in the #GoodnightBloomberg campaign?
No	4 (26.7%)
Yes	11 (73.3%)

#seenorheardofthecampiagn
seenordheard <- sleephygiene %>% filter(Q81_seenorheardfromGNbloombergcampaign == "Yes")

tab16 <- tableby(~ Q81_seenorheardfromGNbloombergcampaign,
                data=seenordheard, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab16, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	Overall (N=54)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?
Don’t know	0 (0.0%)
No	0 (0.0%)
Yes	54 (100.0%)

sleephygiene <- sleephygiene %>% mutate(Engagementyesno = case_when(
  Q69_didyouengagewiththecampaign == "Yes" ~ 1,
  Q69_didyouengagewiththecampaign == "No" ~ 0,
  Q69_didyouengagewiththecampaign == "Don't know" ~ 0,
  is.na(Q69_didyouengagewiththecampaign) ~ NA_real_)) %>%
  mutate(Engagementyesno = factor(Engagementyesno))

tab1 <- tableby(Engagementyesno ~ Q3_role + 
                  Q4_gender +
                  Q5_age +
                  Q6_numberinhousehold +
                  Q37_employed +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q9_howoftensleepypastmonth +
                  Q61_howoftensleepypasttwoweeks +
                  Q84_awareofhowtoimprovesleepquality +
                  Q81_seenorheardfromGNbloombergcampaign +
                  Q96_picture1 +
                  Q96_picture2 +
                  Q96_picture3 +
                  Q96_picture4 +
                  Q96_picture5 +
                  Q96_picture6 +
                  Q96_picture7 +
                  Q96_picture8 +
                  Q95_talkedtoanyone +
                  Q82_knowanyonewhoengaged +
                  Q69_didyouengagewiththecampaign +
                  Q67_move30minutes +
                  Q67_breathing +
                  Q67_powerdown +
                  Q68_timing + 
                  Q79_moresuccessfuloutcomsuggestions +
                  Q59_canmaintainhealthysleephabits +
                  Q59_cancutoutscreen +
                  Q59_canexercise +
                  Q59_canparticipateinbreathing +
                  Q44_goodnightsleepisimportant +
                  Q44_mentalclarity +
                  Q44_feelpositive +
                  Q44_cuttingoutscreenleadstobettersleep +
                  Q44_exercisingleadstobettersleep +
                  Q44_breathingexercisesleadstobettersleep +
                  Q44_iwillstopscreens +
                  Q44_iwillexercise +
                  Q44_iwillbreathe,
                data=sleephygiene, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	0 (N=119)	1 (N=25)	Total (N=144)	p value
What is your role at Bloomberg
N-Miss	0	2	2
Faculty/Staff Member	9 (7.6%)	0 (0.0%)	9 (6.3%)
Full-time student	65 (54.6%)	16 (69.6%)	81 (57.0%)
Not affiliated with Bloomberg School of Public Health	0 (0.0%)	0 (0.0%)	0 (0.0%)
Part-time student	45 (37.8%)	7 (30.4%)	52 (36.6%)
Which best describes your gender identity?				0.550¹
N-Miss	0	2	2
Female	98 (82.4%)	21 (91.3%)	119 (83.8%)
Male	20 (16.8%)	2 (8.7%)	22 (15.5%)
Non-binary / third gender	1 (0.8%)	0 (0.0%)	1 (0.7%)
How old are you?				0.995¹
N-Miss	0	2	2
18-25	37 (31.1%)	7 (30.4%)	44 (31.0%)
26-34	51 (42.9%)	10 (43.5%)	61 (43.0%)
35-44	19 (16.0%)	4 (17.4%)	23 (16.2%)
45-54	10 (8.4%)	2 (8.7%)	12 (8.5%)
55-64	1 (0.8%)	0 (0.0%)	1 (0.7%)
64-75	1 (0.8%)	0 (0.0%)	1 (0.7%)
How many people live in your household, including yourself?				0.011²
Median (Q1, Q3)	2.00 (1.00, 3.00)	3.00 (2.00, 4.00)	2.00 (2.00, 3.00)
If you are a student at Bloomberg, are you currently employed outside of your education program?				0.024¹
N-Miss	0	2	2
N/A - I am not a student at Bloomberg	8 (6.7%)	0 (0.0%)	8 (5.6%)
No	59 (49.6%)	6 (26.1%)	65 (45.8%)
Yes	52 (43.7%)	17 (73.9%)	69 (48.6%)
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?				0.752²
Median (Q1, Q3)	7.00 (6.00, 7.00)	7.00 (6.00, 8.00)	7.00 (6.00, 7.00)
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?				0.183²
Median (Q1, Q3)	8.00 (7.00, 8.00)	8.00 (7.00, 9.00)	8.00 (7.00, 8.00)
How often did you feel sleepy during the day in the past month?
N-Miss	43	10	53
Never	3 (3.9%)	0 (0.0%)	3 (3.3%)
Rarely	10 (13.2%)	3 (20.0%)	13 (14.3%)
Sometimes	56 (73.7%)	10 (66.7%)	66 (72.5%)
Very often	0 (0.0%)	0 (0.0%)	0 (0.0%)
Always	7 (9.2%)	2 (13.3%)	9 (9.9%)
How often did you feel sleepy during the day during the past 2 weeks?
N-Miss	42	9	51
Never	2 (2.6%)	0 (0.0%)	2 (2.2%)
Rarely	17 (22.1%)	5 (31.2%)	22 (23.7%)
Sometimes	45 (58.4%)	9 (56.2%)	54 (58.1%)
Very often	0 (0.0%)	0 (0.0%)	0 (0.0%)
Always	13 (16.9%)	2 (12.5%)	15 (16.1%)
Do you know any ways a person can improve their sleep quality?				0.214¹
No	7 (5.9%)	0 (0.0%)	7 (4.9%)
Yes	112 (94.1%)	25 (100.0%)	137 (95.1%)
In the last two-three weeks have you heard, seen, or received any information from the #GoodnightBloomberg campaign led by JHSPH students promoting better sleep?				< 0.001¹
Don’t know	32 (26.9%)	1 (4.0%)	33 (22.9%)
No	57 (47.9%)	0 (0.0%)	57 (39.6%)
Yes	30 (25.2%)	24 (96.0%)	54 (37.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 1				< 0.001¹
N-Miss	14	3	17
No	13 (12.4%)	11 (50.0%)	24 (18.9%)
Not sure	88 (83.8%)	9 (40.9%)	97 (76.4%)
Yes	4 (3.8%)	2 (9.1%)	6 (4.7%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 2				< 0.001¹
N-Miss	11	1	12
No	7 (6.5%)	0 (0.0%)	7 (5.3%)
Not sure	74 (68.5%)	2 (8.3%)	76 (57.6%)
Yes	27 (25.0%)	22 (91.7%)	49 (37.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 3				< 0.001¹
N-Miss	13	3	16
No	12 (11.3%)	8 (36.4%)	20 (15.6%)
Not sure	92 (86.8%)	9 (40.9%)	101 (78.9%)
Yes	2 (1.9%)	5 (22.7%)	7 (5.5%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 4				< 0.001¹
N-Miss	14	3	17
No	11 (10.5%)	7 (31.8%)	18 (14.2%)
Not sure	88 (83.8%)	10 (45.5%)	98 (77.2%)
Yes	6 (5.7%)	5 (22.7%)	11 (8.7%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 5				< 0.001¹
N-Miss	13	2	15
No	11 (10.4%)	3 (13.0%)	14 (10.9%)
Not sure	90 (84.9%)	7 (30.4%)	97 (75.2%)
Yes	5 (4.7%)	13 (56.5%)	18 (14.0%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 6				0.030¹
N-Miss	12	3	15
No	13 (12.1%)	6 (27.3%)	19 (14.7%)
Not sure	92 (86.0%)	14 (63.6%)	106 (82.2%)
Yes	2 (1.9%)	2 (9.1%)	4 (3.1%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 7				< 0.001¹
N-Miss	13	2	15
No	14 (13.2%)	3 (13.0%)	17 (13.2%)
Not sure	90 (84.9%)	10 (43.5%)	100 (77.5%)
Yes	2 (1.9%)	10 (43.5%)	12 (9.3%)
Were these materials were utilized in our #GoodnightBloomberg campaign? Picture 8				0.001¹
N-Miss	13	3	16
No	13 (12.3%)	5 (22.7%)	18 (14.1%)
Not sure	91 (85.8%)	13 (59.1%)	104 (81.2%)
Yes	2 (1.9%)	4 (18.2%)	6 (4.7%)
Have you talked to anyone about the #GoodnightBloomberg campaign?				< 0.001¹
No	117 (98.3%)	14 (56.0%)	131 (91.0%)
Yes	2 (1.7%)	11 (44.0%)	13 (9.0%)
Do you know anyone who engaged in any way with the #GoodnightBloomberg campaign about promoting better sleep?				< 0.001¹
No	115 (96.6%)	19 (76.0%)	134 (93.1%)
Yes	4 (3.4%)	6 (24.0%)	10 (6.9%)
Did you engage in any way with the #GoodnightBloomberg campaign led by JHSPH students during the past 2 weeks?				< 0.001¹
No	119 (100.0%)	0 (0.0%)	119 (82.6%)
Yes	0 (0.0%)	25 (100.0%)	25 (17.4%)
In the last two weeks, how many days did you participate in the following techniques? Move 30 minutes total per day				0.286²
Median (Q1, Q3)	9.00 (5.00, 12.00)	8.00 (4.00, 10.00)	9.00 (5.00, 12.00)
In the last two weeks, how many days did you participate in the following techniques? Use a breathing exercise				0.419²
Median (Q1, Q3)	2.50 (1.00, 6.00)	3.00 (2.00, 6.00)	2.50 (1.00, 6.00)
In the last two weeks, how many days did you participate in the following techniques? Power down your screens (i.e. cell phone, tablet, computer, TV) 1 hour before bed				0.419²
Median (Q1, Q3)	2.50 (1.00, 6.00)	3.00 (2.00, 6.00)	2.50 (1.00, 6.00)
Was the timing of the texts/posts convenient for you to adopt the recommended activity?				0.040¹
N-Miss	26	3	29
No	48 (51.6%)	6 (27.3%)	54 (47.0%)
Yes	45 (48.4%)	16 (72.7%)	61 (53.0%)
I think I would have had a more successful outcome (e.g. better sleep quality) if (choose all that may apply):				0.047¹
N-Miss	41	1	42
I had more flexibility in my day	36 (46.2%)	6 (25.0%)	42 (41.2%)
The campaign was longer	14 (17.9%)	10 (41.7%)	24 (23.5%)
There was an in-person/on-campus component to the campaign	18 (23.1%)	7 (29.2%)	25 (24.5%)
There were subject matter experts checking in with me one-on-one	10 (12.8%)	1 (4.2%)	11 (10.8%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can maintain healthy sleep habits.				0.361¹
N-Miss	0	2	2
Not at all confident	21 (17.6%)	5 (21.7%)	26 (18.3%)
Somewhat confident	75 (63.0%)	11 (47.8%)	86 (60.6%)
Extremely confident	23 (19.3%)	7 (30.4%)	30 (21.1%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can cut out screen use 1 hour before bed.				0.471¹
N-Miss	0	2	2
Not at all confident	56 (47.1%)	14 (60.9%)	70 (49.3%)
Somewhat confident	47 (39.5%)	7 (30.4%)	54 (38.0%)
Extremely confident	16 (13.4%)	2 (8.7%)	18 (12.7%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can exercise for 30 minutes total each day.				0.394¹
N-Miss	0	2	2
Not at all confident	14 (11.8%)	4 (17.4%)	18 (12.7%)
Somewhat confident	54 (45.4%)	7 (30.4%)	61 (43.0%)
Extremely confident	51 (42.9%)	12 (52.2%)	63 (44.4%)
Please tell us how confident you feel practicing the following behaviors in order to get better sleep: I can participate in a breathing exercise during the day or before bed.				0.830¹
N-Miss	1	1	2
Not at all confident	15 (12.7%)	2 (8.3%)	17 (12.0%)
Somewhat confident	62 (52.5%)	13 (54.2%)	75 (52.8%)
Extremely confident	41 (34.7%)	9 (37.5%)	50 (35.2%)
Please rate your agreement with the following statements: Getting a good night’s sleep is important to me.
N-Miss	0	2	2
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	1 (0.8%)	0 (0.0%)	1 (0.7%)
Neither agree nor disagree	1 (0.8%)	0 (0.0%)	1 (0.7%)
Somewhat agree	23 (19.3%)	2 (8.7%)	25 (17.6%)
Strongly agree	94 (79.0%)	21 (91.3%)	115 (81.0%)
Please rate your agreement with the following statements: Having a regular sleep routine improves mental clarity/sharpness.
N-Miss	1	1	2
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	1 (0.8%)	0 (0.0%)	1 (0.7%)
Neither agree nor disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat agree	18 (15.3%)	5 (20.8%)	23 (16.2%)
Strongly agree	99 (83.9%)	19 (79.2%)	118 (83.1%)
Please rate your agreement with the following statements: I feel positive about the quality of my sleep.				0.945¹
N-Miss	0	2	2
Strongly disagree	9 (7.6%)	2 (8.7%)	11 (7.7%)
Somewhat disagree	28 (23.5%)	5 (21.7%)	33 (23.2%)
Neither agree nor disagree	20 (16.8%)	3 (13.0%)	23 (16.2%)
Somewhat agree	42 (35.3%)	10 (43.5%)	52 (36.6%)
Strongly agree	20 (16.8%)	3 (13.0%)	23 (16.2%)
Please rate your agreement with the following statements: I think cutting out screen use 1 hour before bed leads to better sleep.				0.807¹
N-Miss	0	1	1
Strongly disagree	1 (0.8%)	0 (0.0%)	1 (0.7%)
Somewhat disagree	5 (4.2%)	0 (0.0%)	5 (3.5%)
Neither agree nor disagree	16 (13.4%)	3 (12.5%)	19 (13.3%)
Somewhat agree	40 (33.6%)	10 (41.7%)	50 (35.0%)
Strongly agree	57 (47.9%)	11 (45.8%)	68 (47.6%)
Please rate your agreement with the following statements: I think exercising regularly leads to better sleep.
N-Miss	0	1	1
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	2 (1.7%)	0 (0.0%)	2 (1.4%)
Neither agree nor disagree	4 (3.4%)	1 (4.2%)	5 (3.5%)
Somewhat agree	32 (26.9%)	8 (33.3%)	40 (28.0%)
Strongly agree	81 (68.1%)	15 (62.5%)	96 (67.1%)
Please rate your agreement with the following statements: I think participating in breathing exercises during the day or before bed leads to better sleep.
N-Miss	0	1	1
Strongly disagree	0 (0.0%)	0 (0.0%)	0 (0.0%)
Somewhat disagree	3 (2.5%)	2 (8.3%)	5 (3.5%)
Neither agree nor disagree	29 (24.4%)	7 (29.2%)	36 (25.2%)
Somewhat agree	48 (40.3%)	9 (37.5%)	57 (39.9%)
Strongly agree	39 (32.8%)	6 (25.0%)	45 (31.5%)
Please rate your agreement with the following statements: In the next two weeks, I will stop using screens 1 hour before bed for better sleep.				0.879¹
N-Miss	1	2	3
Strongly disagree	22 (18.6%)	5 (21.7%)	27 (19.1%)
Somewhat disagree	24 (20.3%)	3 (13.0%)	27 (19.1%)
Neither agree nor disagree	24 (20.3%)	4 (17.4%)	28 (19.9%)
Somewhat agree	34 (28.8%)	7 (30.4%)	41 (29.1%)
Strongly agree	14 (11.9%)	4 (17.4%)	18 (12.8%)
Please rate your agreement with the following statements: In the next two weeks, I will exercise for at least 30 minutes total each day for better sleep.				0.329¹
N-Miss	0	2	2
Strongly disagree	3 (2.5%)	0 (0.0%)	3 (2.1%)
Somewhat disagree	5 (4.2%)	3 (13.0%)	8 (5.6%)
Neither agree nor disagree	16 (13.4%)	1 (4.3%)	17 (12.0%)
Somewhat agree	41 (34.5%)	8 (34.8%)	49 (34.5%)
Strongly agree	54 (45.4%)	11 (47.8%)	65 (45.8%)
Please rate your agreement with the following statements: In the next two weeks, I will do a daily breathing exercise for better sleep.				0.989¹
N-Miss	0	2	2
Strongly disagree	10 (8.4%)	2 (8.7%)	12 (8.5%)
Somewhat disagree	17 (14.3%)	4 (17.4%)	21 (14.8%)
Neither agree nor disagree	22 (18.5%)	4 (17.4%)	26 (18.3%)
Somewhat agree	47 (39.5%)	8 (34.8%)	55 (38.7%)
Strongly agree	23 (19.3%)	5 (21.7%)	28 (19.7%)

Pearson’s Chi-squared test
Kruskal-Wallis rank sum test

sleephygienepre <- readRDS(file="foranalysis.rds")

sleephygienepre <- sleephygienepre %>% 
  mutate(Q5_age = case_when(
    Q5_age >= 18 & Q5_age <= 25 ~ "18-25",
    Q5_age >= 26 & Q5_age <= 34 ~ "26-34",
    Q5_age >= 35 & Q5_age <= 44 ~ "35-44",
    Q5_age >= 45 & Q5_age <= 54 ~ "45-54",
    Q5_age >= 55 & Q5_age < 64 ~ "55-64",
    Q5_age >= 64 & Q5_age <= 75 ~ "64-75",
    Q5_age > 75 ~ "75+",
    is.na(Q5_age) ~ NA_character_
  )) %>% 
  mutate(Q5_age = factor(Q5_age)) %>%
  mutate(post = 0) %>% 
  mutate(
    Q10_hoursofsleeplast5workdays = Q10_workdayhoursofsleep,
    Q10_hoursofsleeppastweekend = Q11_weekendhoursofsleep,
    Q61_howoftensleepypasttwoweeks = Q9_howoftensleepy
  ) %>%
  select(post, Q3_role, Q2_program, Q4_gender, Q5_age, Q6_numberinhousehold, Q10_hoursofsleeplast5workdays, Q10_hoursofsleeppastweekend, Q61_howoftensleepypasttwoweeks) 
  
sleephygienepost <- sleephygiene %>% mutate(post = 1) %>% select(post, Q3_role, Q2_program, Q4_gender, Q5_age, Q6_numberinhousehold, Q10_hoursofsleeplast5workdays, Q10_hoursofsleeppastweekend, Q61_howoftensleepypasttwoweeks) 

sleephygienepreandpost <- rbind(sleephygienepre, sleephygienepost)

sleephygienepreandpost <- sleephygienepreandpost %>% mutate(Q61_smaller = case_when(
  is.na(Q61_howoftensleepypasttwoweeks) ~ NA_character_,
  Q61_howoftensleepypasttwoweeks == "Never" ~ "Never",
  Q61_howoftensleepypasttwoweeks == "Rarely" ~ "Rarely",
  Q61_howoftensleepypasttwoweeks == "Sometimes" ~ "Sometimes",
  Q61_howoftensleepypasttwoweeks == "Very often" | Q61_howoftensleepypasttwoweeks == "Always" ~ "Very often or Always",
)) %>%
  mutate(Q61_smaller = factor(Q61_smaller)) %>%
  mutate(Q2_program = case_when(
  Q2_program == "Post-doctoral student" ~ as.character("Post doctoral student"),
  TRUE ~ as.character(Q2_program)
  )) %>%
  mutate(Q2_program = factor(Q2_program))

tab1 <- tableby(post ~ Q3_role +
                  Q2_program + 
                  Q4_gender + 
                  Q5_age + 
                  Q6_numberinhousehold +
                  Q10_hoursofsleeplast5workdays +
                  Q10_hoursofsleeppastweekend +
                  Q61_smaller,
                data=sleephygienepreandpost, test=TRUE, total=TRUE, 
                numeric.stats=c("medianq1q3"), numeric.test="kwt", cat.test="chisq")
summary(tab1, title='Table 1. Baseline information', pfootnote=TRUE, digits = 2)

Table 1. Baseline information
	0 (N=209)	1 (N=149)	Total (N=358)	p value
Q3_role				0.079¹
N-Miss	3	4	7
Faculty/Staff Member	6 (2.9%)	9 (6.2%)	15 (4.3%)
Full-time student	140 (68.0%)	82 (56.6%)	222 (63.2%)
Part-time student	60 (29.1%)	53 (36.6%)	113 (32.2%)
Not affiliated with Bloomberg School of Public Health	0 (0.0%)	1 (0.7%)	1 (0.3%)
Q2_program				0.009¹
N-Miss	9	14	23
Doctoral Student	54 (27.0%)	29 (21.5%)	83 (24.8%)
Masters Student	140 (70.0%)	90 (66.7%)	230 (68.7%)
Other	1 (0.5%)	6 (4.4%)	7 (2.1%)
Post doctoral student	5 (2.5%)	10 (7.4%)	15 (4.5%)
Q4_gender				0.617¹
N-Miss	3	4	7
Female	166 (80.6%)	121 (83.4%)	287 (81.8%)
Male	35 (17.0%)	23 (15.9%)	58 (16.5%)
Non-binary / third gender	4 (1.9%)	1 (0.7%)	5 (1.4%)
Prefer not to say	1 (0.5%)	0 (0.0%)	1 (0.3%)
Q5_age				0.546¹
N-Miss	5	4	9
18-25	64 (31.4%)	44 (30.3%)	108 (30.9%)
26-34	98 (48.0%)	63 (43.4%)	161 (46.1%)
35-44	32 (15.7%)	24 (16.6%)	56 (16.0%)
45-54	9 (4.4%)	12 (8.3%)	21 (6.0%)
55-64	1 (0.5%)	1 (0.7%)	2 (0.6%)
64-75	0 (0.0%)	1 (0.7%)	1 (0.3%)
How many people live in your household, including yourself?				0.146²
Median (Q1, Q3)	2.00 (2.00, 3.00)	2.00 (2.00, 3.00)	2.00 (2.00, 3.00)
During the past 5 workdays, how many hours of sleep did you get per night on average?				0.731²
Median (Q1, Q3)	7.00 (6.00, 7.50)	7.00 (6.00, 7.00)	7.00 (6.00, 7.50)
During the past weekend, how many hours of sleep did you get per night on average?				0.187²
Median (Q1, Q3)	8.00 (7.00, 9.00)	8.00 (7.00, 8.00)	8.00 (7.00, 9.00)
Q61_smaller				0.098¹
N-Miss	69	54	123
Never	3 (2.1%)	2 (2.1%)	5 (2.1%)
Rarely	27 (19.3%)	23 (24.2%)	50 (21.3%)
Sometimes	99 (70.7%)	54 (56.8%)	153 (65.1%)
Very often or Always	11 (7.9%)	16 (16.8%)	27 (11.5%)

Pearson’s Chi-squared test
Kruskal-Wallis rank sum test

library(sjPlot)
sleephygiene <- sleephygiene %>% mutate(Q69_didyouengagewiththecampaignbinary = case_when(
  Q69_didyouengagewiththecampaign == "No" ~ 0,
  Q69_didyouengagewiththecampaign == "Yes" ~ 1)) %>%
  mutate(Q4_gender_binary = case_when(
    Q4_gender == "Male" ~ 1,
    Q4_gender == "Female" ~ 0,
    TRUE ~ NA_real_
  )) %>%
  mutate(Q4_gender_binary = factor(Q4_gender_binary, labels = c("Female", "Male"))) %>%
  mutate(happywithsleepqualitycombined = case_when(
    Q90_areyouhappywithyoursleepquality_awareofcampaign == "Yes" ~ 1,
    Q90_areyouhappywithyoursleepquality_awareofcampaign == "No" ~ 0,
    Q91_areyouhappywithyoursleepquality_notawareofcampaign == "Yes" ~ 1,
    Q91_areyouhappywithyoursleepquality_notawareofcampaign == "No" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Good" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Excellent" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Poor" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Fair" ~ 0,
  )) %>%
  mutate(happywithsleepqualitycombined = factor(happywithsleepqualitycombined)) %>%
  mutate(Q67_1 = case_when(
    is.na(Q67_1) ~ 0,
    TRUE ~ as.numeric(Q67_1)
  )) %>%
  mutate(Q67_2 = case_when(
    is.na(Q67_2) ~ 0,
    TRUE ~ as.numeric(Q67_2)
  )) %>%
  mutate(Q67_3 = case_when(
    is.na(Q67_3) ~ 0,
    TRUE ~ as.numeric(Q67_3)
  )) %>%
  mutate(pointscombinedperdays = Q67_1 + Q67_2 + Q67_3) %>%
  mutate(ratesleepqualitycombined = case_when(
    Q89_ratesleepquality_notawareofcampaign == "Good" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Excellent" ~ 1,
    Q89_ratesleepquality_notawareofcampaign == "Poor" ~ 0,
    Q89_ratesleepquality_notawareofcampaign == "Fair" ~ 0,
  ))

#Participating in the campaign
mylogit <- glm(Q69_didyouengagewiththecampaignbinary ~ Q4_gender_binary + Q10_hoursofsleeplast5workdays + Q10_hoursofsleeppastweekend, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	Q69_didyouengagewiththecampaignbinary
Predictors	Odds Ratios	CI	p
(Intercept)	0.04	0.00 – 1.15	0.069
Q4_gender_binary: Male	0.53	0.08 – 2.08	0.427
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?	0.86	0.55 – 1.37	0.507
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?	1.40	0.93 – 2.14	0.115
Observations	141
R² Tjur	0.024

#Happy with sleep quality
mylogit <- glm(happywithsleepqualitycombined ~ Q4_gender_binary + Q10_hoursofsleeplast5workdays + Q10_hoursofsleeppastweekend + Q69_didyouengagewiththecampaignbinary, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	happywithsleepqualitycombined
Predictors	Odds Ratios	CI	p
(Intercept)	0.00	0.00 – 0.01	<0.001
Q4_gender_binary: Male	1.54	0.55 – 4.42	0.416
On average, how many hours of sleep did you get per night during the following periods of time: during the last 5 workdays?	2.82	1.78 – 4.79	<0.001
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?	1.05	0.73 – 1.51	0.783
Q69_didyouengagewiththecampaignbinary	1.47	0.51 – 4.26	0.472
Observations	141
R² Tjur	0.209

mylogit <- glm(happywithsleepqualitycombined ~ Q10_hoursofsleeppastweekend + Q4_gender_binary + pointscombinedperdays, family = binomial(link = "logit"), data = sleephygiene)
tab_model(mylogit)

	happywithsleepqualitycombined
Predictors	Odds Ratios	CI	p
(Intercept)	0.01	0.00 – 0.10	<0.001
On average, how many hours of sleep did you get per night during the following periods of time: during the past weekend?	1.64	1.23 – 2.25	0.001
Q4_gender_binary: Male	1.58	0.59 – 4.34	0.367
pointscombinedperdays	1.06	1.01 – 1.12	0.018
Observations	141
R² Tjur	0.108